Preschoolers’ appreciation of speaker vocal affect as a cue to referential intent
Bibliographic record
Abstract
An eye tracking methodology was used to evaluate 3- and 4-year-old children's sensitivity to speaker affect when resolving referential ambiguity. Children were presented with pictures of three objects on a screen (including two referents of the same kind, e.g., an intact doll and a broken doll, and one distracter item), paired with a prerecorded referentially ambiguous instruction (e.g., "Look at the doll"). The intonation of the instruction varied in terms of the speaker's vocal affect: positive-sounding, negative-sounding, or neutral. Analyses of eye gaze patterns indicated that 4-year-olds, but not 3-year-olds, were more likely to look to the referent whose state matched the speaker's vocal affect as the noun was heard (e.g., looked more often to the broken doll referent in the negative affect condition). These findings indicate that 4-year-olds can use speaker affect to help identify referential mappings during on-line comprehension.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".